Reliability Evaluation And Optimization Models Of Power Systems Containing Wind Energy Considering Mutliple Factors

With the increasing exhaustion of traditional energy resources and emission ofnon-environmentally friendly gases, people are actively exploring alternative energyresources which can be used to meet the human energy demand. As a clean andrenewable energy, wind energy is one of the most important alternative energy resources.In the world, many countries have made different policies for encouraging thedevelopment of wind energy resources. With the development of wind power generationtechniques, the scale of wind energy was increasing step by step in the last decade.Generally, wind is considered as a fluctuant and uncontrollable energy resouce due tothe stochastic and intermittent natures of wind speed. Integration of large scale windfarms into a power grid has a significant effect on the security and reliability of powergrid. Therefore, it is necessary for the experts to study the reliabliey assessment modelof wind power systems and to analyze the comprehensive impacts of wind farm on thereliability of power systems. These researches have an important theoretical andpractical significance in the designing, planning and operation of power systemcontaining wind farms.With the scale expanding of wind farm, increasing the number of wind farm,extending collector system topology, and increasing wind turbine generator (WTG)intensity in a wind farm, mutilple factors, such as wind speed wake, multi-dimensionalcorrelations, collector system failures, and wind farm layout, have significant impactson energy production of wind farms and reliability of power systems. The papertheoretically researches the impact of above factors on wind energy production andwind power system reliability under the support in part by the National Natural ScienceFoundation of China (No.51077135)“Probabilistic model and algorithm of wind farmreliability evaluation” and the Natural Science Foundation Project of CQ CSTC (No.CSTC2010BA3006)“Reliability evaluation and optimization models and algorithmsfor power system containing large scale wind energies”.Wind speed and wind direction are the critical influence factors of wake effect,which has a very significant effect on wind energy production of wind farm. Wind speedand wind direction are not completely independent variables; on the contrary, they havea certain conditional dependence relationship between them. Therefore, this conditionaldependence should be considered in the proposed wind speed model to improve theaccuracy. According to the above analysis, wind direction sampling model is built using the empirical distribution of wind direction. A conditionally dependent wind speedmodel is established using the wind wake theory, Weibull model of wind speeds, andconditional dependence between wind speeds and wind directions. The proposed modelcan be used to generate wind speed and wind direction data with a given conditionaldependence. The collected wind speed and wind direction data in the practical regionhave been used to verify the validity and applicability of the proposed model.Correlation and conditional dependence of wind speed and wind direction seriesalways appear in multiple wind farms, which should also be considered in reliabilityevaluation models of power systems containing wind farm. Wind speed correlationmodel and wind direction correlation model are built using normal copula andArchimedean copula in this paper. The empirical copula is used to select a propriatecorrelation model. Clustering method, transformation and interpolation techniques areused to build the conditional dependence model of wind speed and wind direction basedon empirical distribution and Weibull distribution models. Then, wind speed and winddirection generation model considering their correlation and conditional dependence isobtained. The proposed model is verified using the observed wind data, and resultsshow that simulated and observed wind data have an identical features in correlation,conditional dependence, statistics characteristics, and distribution characteristics. Inother words, the results have verified the validity and availability of the proposedmodel.Besides WTG failures in a wind farm, other factors, such as the failures ofelectrical collector system (ECS), disconnection and switching operation of switchdevices, and different collector system topologies, also have effects on energyproduction of a wind farm. There are relatively little studies on the comprehensiveimpact on the reliability of wind power system. Novel indices for describing thereliability of wind farm ECS are presented based on the topologies of wind farm in thispaper. The concept of section for a partitioning wind farm ECS is defined. A reliabilityevaluation model of wind farm ECS is built using the state enumeration algorithm andmatrix operations. The proposed model can not only considers the multi-failure of ECScomponents, including failures of cable feeder, WTG and wind turbine transformer, butalso consider the operational states of switching devices in failure, disconnection andswitching processes. Four different wind farm ECS topologies are implemented usingproposed model. Case studies on the reliability evaluation of wind farm ECS are used toverify the feasibility and validity of the proposed technique. The proposed technique isvery significant and valuable on wind farm collector system planning. Energy production of a wind farm is considerably affected by wake effect.Therefore, in wind farm planning, it is essential to optimize the WTGs’ layout fordecreasing the effect of wake effect and increasing the energy production of wind farm.A geometric theory is used to determine the upstream WTGs and calculate thehorizontal and deviation distances between any two WTGs along the wind direction. Aparticle swarm optimization algorithm with the shrinkage factor and mutation factor isused to obtain the optimal solution with maximum energy production of a wind farm.The discrete joint distribution probability of wind direction and wind speed isincorporated into the optimization process. Based on the proposed technique, theoptimal wind farm layout can be obtained using the historical wind speed and winddirection data of the practical region. A modified reliability test system containing awind farm with the optimal layout is used to evaluate the reliability of a generationsystem. The results show that the proposed technique is effective to decrease the wakeeffect, to increase the energy production of wind farm, and to improve the reliability ofpower system.Compared with conventional generators, wind power is fluctuant andnon-dispatched. The existing researches on reliability of power system with wind farmcan always consider the contribution of wind power on power system adequacy, butthese researches cannot consider the negative impact of wind power fluctuation onpower system reliability. When the power system operates in the steady-state, the taskof power system is not only to meet load demand, but also to implement real timeadjustment when generation side or demand side is suffered from a disturbance.Therefore, according to the steady state operation characteristic of power system, thepaper presents a reliability evaluation model of power system with wind farmconsidering steady-state frequency characteristics. The fluctuation of wind power can bereflected by the proposed model. The model is built by the load power equivalence, thestate simulation of conventional generator, and the steady-state frequency adjustment.The proposed model is applied to reliability test system, and the results show that theproposed method can not only reflect the contribution of wind power to the overallpower system reliability, but also reflect the negative impact of wind power fluctuationon power system reliability.